1. Field of the Invention
This invention relates generally to techniques for converting analog signals into digital signals, and, more particularly, to techniques for correcting errors in sampled data acquired from time-interleaved analog-to-digital converters.
2. Description of Related Art
In many applications, a need arises for converting analog signals into corresponding digital codes. One of these applications is automatic test equipment, or ATE. ATE systems are generally complex electronic systems for verifying the operation of electronic devices or assemblies.
FIG. 1 is a high level block diagram of an ATE system, or “tester.” A host computer 110 runs a test program developed for testing a unit under test, or UUT 118. The host computer 110 interactively communicates with a clock distribution circuit 112 and source/capture instruments 114. These instruments provide stimuli to and monitor responses from the UUT 118 via an interconnect 116. Examples of testers are well known in the art, and include the Catalyst™, Tiger™, Panther™, FLEX™ and UltraFLEX™ test systems designed by Teradyne, Inc. of North Reading, Mass.
In ATE as well as other applications, electronic signals are generally converted from analog to digital form through the use of devices called analog-to-digital converters, or ADCs. An ADC is a device that generally has an analog input, for receiving an analog signal to be converted, and a digital output, for providing a converted, digital rendition of the analog signal. Conversions take place at precise instants of time, as defined by a clock signal applied to a clock input of the ADC.
An ADC is generally clocked at a fixed sampling rate, FS. As is known, the maximum frequency that an ADC can unambiguously represent is limited by Shannon's Theory to one-half the sampling rate. This frequency, FS/2, is commonly called the “Nyquist rate.”
More generally, ADCs can unambiguously represent analog signals over any maximum bandwidth of FS/2. Outside this bandwidth, a phenomenon called “aliasing” occurs, wherein frequency content outside the band folds back and superimposes within the band. Aliasing is generally regarded as an error, and the analog input signal is typically band limited (filtered) to avoid aliasing.
An important specification of an ADC is its maximum sampling rate—the maximum clock frequency that the device can handle before it fails to operate or errors occur. Because the Nyquist rate is half the sampling rate, the maximum sampling rate directly limits the maximum frequency that an ADC can unambiguously capture.
To overcome this limitation, designers have developed circuits consisting of many ADCs operated concurrently. An example of this type of circuit, called a parallel, time-interleaved converter, or “PTIC,” is shown in FIG. 2. There, M different ADCs 210a-210m have their analog inputs connected together to receive the same input signal, Analog In. A buffer amplifier (not shown) is often provided at the input of each ADC. A clock generator, such as the clock distribution circuit 112, provides a clock signal to each of the ADCs. The clock signals are operated at the same frequency, FS, but are uniformly spaced in time, such that the delay between successive clocks is approximately 1/MFS. A sequencer 212 receives the digital signals from the M ADCs and outputs them, in the order in which they are converted, to produce a combined output signal, Digital Out. Although each ADC operates at a rate of only FS, the circuit as a whole operates at MFS, i.e., a new sample is generated every 1/MFS seconds. The sampling rate, and therefore the Nyquist rate, is effectively increased by a factor of M.
To analyze spectral content of captured signals, the PTIC 200 includes a capture memory 214 and a Discrete Fourier Transform, or “DFT” unit 216. The capture memory 214 holds sequences of sampled signals from Digital Out, and the DFT unit 216 transforms the sampled sequences into power spectra.
This parallel, time-interleaved approach has been used with great success for decades. However, certain obstacles have limited its application. For instance, it is known that different converters are never precisely identical. This is true even when converters are nominally of the same type (e.g., the same manufacturer, model, and grade). Differences between converters cause each of them to convert the analog input signal in slightly different ways. These differences introduce errors in Digital Out. Also, the clock signals feeding the different converters are never exactly aligned with their ideal positions. There is always some timing skew, and this skew introduces additional errors.
Circuit designers have previously developed techniques for correcting errors among the different converters. For instance, developers have prescribed calibration procedures for correcting offset, gain, and phase. For correcting offset errors, offset errors are measured for each converter prior to operation. During operation, samples are individually corrected by subtracting the measured offsets. Gain errors have been addressed in a similar way, by measuring gain errors of each converter and applying them to correct individual samples. Phase errors have also been addressed, by slightly delaying or advancing clock signals to each converter. These errors, extremely pronounced in the frequency domain as spur components, increase as discrepancies between converters become greater.
Although these techniques have achieved some degree of effectiveness, they are far from optimal. For example, they do not generally account for variations in gain and phase that change with input signal frequency. Therefore, corrections that work for one input frequency often do not work optimally for different input frequencies.
What is needed is a way of correcting for errors among converters in parallel, interleaved topologies, which accounts for the frequency dependency of gain and phase.